An Embedded Vision Tool for Volcanic Ash Analysis

Abstract

The ash fall-out following explosion activity of volcanoes represents serious hazard for both road and air traffic. In this paper the development of a low-cost vision system for the monitoring of ash fall-out phenomena by measuring ash granulometry is reported. The proposed methodology is based on a suitable image processing paradigm that has been implemented in Python/Open CV on an embedded, single board computer architecture, Raspberry Pi 4 Model B and a Pi Camera module v2.1. The design and realization of a prototype are reported. Experimental investigations have been performed using reference images.